Research Metrics

In Scholarly Metrics Under the Microscope, editors Blaise Cronin and Cassidy R. Sugimoto bring together and expertly annotate a wealth of previously published papers, harvested from a wide range of journals and disciplines, that provide critical commentary on the use of metrics, both established and emerging, to assess the quality of scholarship and the impact of research. The expansive overview and analysis presented in this remarkable volume will be welcomed by any scholar or researcher who seeks a deeper understanding of the role and significance of performance metrics in higher education, research evaluation, and science policy.

Starting with the essential histories of bibliometrics and altmetrics, and continuing with in-depth descriptions of the core tools and emerging issues at stake in the future of both fields, Meaningful Metrics is a convenient all-in-one resource that is designed to be used by a range of readers, from those with little to no background on the subject to those looking to become movers and shakers in the current scholarly metrics movement.

A comprehensive, state-of-the-art examination of the changing ways we measure scholarly performance and research impact. Bibliometrics has moved well beyond the mere tracking of bibliographic citations. The web enables new ways to measure scholarly productivity and impact, making available tools and data that can reveal patterns of intellectual activity and impact that were previously invisible: mentions, acknowledgments, endorsements, downloads, recommendations, blog posts, tweets. This book describes recent theoretical and practical advances in metrics-based research, examining a variety of alternative metrics--or "altmetrics"--while also considering the ethical and cultural consequences of relying on metrics to assess the quality of scholarship. Once the domain of information scientists and mathematicians, bibliometrics is now a fast-growing, multidisciplinary field that ranges from webometrics to scientometrics to influmetrics. The contributors to Beyond Bibliometrics discuss the changing environment of scholarly publishing, the effects of open access and Web 2.0 on genres of discourse, novel analytic methods, and the emergence of next-generation metrics in a performance-conscious age.

Measuring Research: What Everyone Needs to KnowRG will provide, for the first time, an accessible account of the methods used to gather and analyze data on research output and impact. Following a brief history of scholarly communication and its measurement - from traditional peer review to crowdsourced review on the social web - the book will look at the classification of knowledge and academic disciplines, the differences between citations and references, the role of peer review, national research evaluation exercises, the tools used to measure research, the many different types of measurement indicators, and how to measure interdisciplinarity. The book also addresses emerging issues within scholarly communication,including whether or not measurement promotes a "publish or perish" culture, fraud in research, or "citation cartels." It will also look at the stakeholders behind these analytical tools, the adverse effects of these quantifications, and the future of research measurement.

Focusing on the guiding principles of presenting data in evidence-based ways so that audiences are effectively engaged and researchers are better understood, Evergreen's exciting new book offers the best communication strategies available to anyone working with data. Indeed, with this highly accessible step-by-step guide, anyone--from students developing a research poster for a school project to faculty and researchers presenting data findings at a conference--can learn how to present and communicate their research findings in more interesting and effective ways.

In today's data-driven world, professionals need to know how to express themselves in the language of graphics effectively and eloquently. Yet information graphics is rarely taught in schools or is the focus of on-the-job training. Now, for the first time, Dona M. Wong, a student of the information graphics pioneer Edward Tufte, makes this material available for all of us. In this book, you will learn: to choose the best chart that fits your data; the most effective way to communicate with decision makers when you have five minutes of their time; how to chart currency fluctuations that affect global business; how to use color effectively; how to make a graphic "colorful" even if only black and white are available.

Designing a complete visualization system involves many subtle decisions. When designing a complex, real-world visualization system, such decisions involve many types of constraints, such as performance, platform (in)dependence, available programming languages and styles, user-interface toolkits, input/output data format constraints, integration wi

Don't simply show your data--tell a story with it! Storytelling with Data teaches you the fundamentals of data visualization and how to communicate effectively with data. You'll discover the power of storytelling and the way to make data a pivotal point in your story.

The classic book on statistical graphics, charts, tables. Theory and practice in the design of data graphics, 250 illustrations of the best (and a few of the worst) statistical graphics, with detailed analysis of how to display data for precise, effective, quick analysis.

Written for individuals in both academic and practice settings, the guide addresses, step-by-step, the fundamental principles for effectively securing funding. It is the only book to provide grant-writing information that encompasses many disciplines and to focus on building a research career with grant writing as a step-wise process. It provides detailed, time-tested strategies for building an investigative team, highlights the challenges of collaboration, and describes how to determine the expertise needed for a team and the roles of co-investigators. The book addresses the needs of both novice and more experienced researchers.

This book presents an accessible introduction to data-driven storytelling. Resulting from unique discussions between data visualization researchers and data journalists, it offers an integrated definition of the topic, presents vivid examples and patterns for data storytelling, and calls out key challenges and new opportunities for researchers and practitioners.

In this volume, Tufte illustrates not only traditional areas such as statistics, repetitions, and multiples but also magic and compositional allegories.